The subject matter of this disclosure relates generally to sensing and, more particularly, to photonic sensors for in situ selective detection of components in fluids, such as methane in an industrial fluid.
Colorimetric gas sensing is a well-established methodology known for almost a century. In colorimetric gas sensing, there are diverse forms of colorimetric sensing materials such as sensing films, sensing tapes, sensing chips, sensing fibers, and others. These and other colorimetric sensing materials operate on two different basic principles.
The first principle involves chemical means of color formation by chemical dyes, pigments, polymers, and other chemicals where the color is produced due to the specific chemical structure of the material. The color change of the sensing material is further induced by a certain gas upon interaction of this gas and the sensing material where the interaction ranges from weak to strong interaction forces. The classification and strengths of interactions between molecules of a gas and molecules of the sensing material are well established and range from weak to strong interactions. Non-limiting examples of such interactions include covalent or ionic bond formation, ligand coordination, electrostatic ion-ion and proton acid-base interactions, hydrogen bonding, halogen bonding, charge-transfer and π-π molecular complexation, dipolar and multipolar interactions, and van der Waals interactions (e.g., physical adsorption). This principle of chemical means of color formation for gas detection is well established. Attractive features include (1) availability of different known chemistries for different gases and (2) known fabrication methods of such colorimetric sensors. However, serious limitations of such sensors include inability to measure some simple small molecule gases for which there are no chemical interactions available.
The second principle involves chemical means of color formation by physical principles of light interactions with optical materials and involves light interference, diffraction, scattering, and combinations thereof. Known photonic resonant vapor sensors operate on univariate vapor quantitation principles based either on the detection of wavelength shift of the resonance peak or change in signal intensity. These sensors are based on porous silicon, self-assembled colloidal particles, mesoporous photonic crystals, inverse opals as well as high-Q resonators. These types of sensors have been demonstrated for different gases, including hydrocarbon gases such as methane, ethane and others. The significant limitation of photonic resonant vapor sensors that operate on univariate vapor quantitation principles is in their cross-sensitivity to other gases in atmosphere. Such cross-sensitivity reduces accuracy of gas detection and increases the likelihood of false alarms that are unacceptable in demanding applications such as in situ detection of methane leaks in various equipment types e.g. gate and compressor stations, machine halls, valves, pressure relief valves, connectors, flanges, and others as well as along the pipelines.
Fugitive methane detection is gaining strong attention in the industrial arena. This is primarily driven by growing regulatory measures to mitigate these emissions for environmental protection and also gas monetization. However, mitigation is driven by detection. Across the economy, there are multiple sectors in which methane emissions can be reduced, from coal mines and landfills to agriculture and oil and gas development. For example, in the agricultural sector, over the last three years, the Environmental Protection Agency (EPA) and the Department of Agriculture have worked with the dairy industry to increase the adoption of methane digesters through loans, incentives, and other assistance. In addition, when it comes to the oil and gas sector, reducing emissions and enhancing economic productivity are becoming quite important. For example, work is underway to advance the production of oil and gas in the Bakken while helping to reduce venting and flaring.
Based on EPA studies, methane emissions accounted for nearly 10 percent of U.S. greenhouse gas emissions in 2012, of which nearly 30 percent came from the production, transmission and distribution of oil and natural gas. EPA found that main emission sources in Oil and Gas operations included gate and compressor stations, machine halls, gate valves, pressure relief valves, control valves, connectors, flanges, casing, wellheads and others as well as along the pipelines networks especially where pipe meets and forms a connection. These sources of emissions are projected to rise more than 25 percent by 2025 without additional steps to lower them. Reducing methane emissions means capturing valuable fuel that is otherwise wasted and reducing other harmful pollutants—a win for public health and the economy. Achieving the Administration's goal would save up to 180 billion cubic feet of natural gas in 2025, enough to heat more than 2 million homes for a year. For these reasons, a strategy for cutting methane emissions from the oil and gas sector is an important component of efforts to address climate change. As part of this strategy, methane detection is considered as the cornerstone to reduce emissions from oil and gas sector. Methane Detection technologies have to be cost effective, reliable, and safe for the oil and gas customers to adopt, use, and rely on.
While there are many commercially available sensors that detect methane and other fluids, there remain long felt needs including, but are not limited to: visual-indicator and machine-indicator-sensors that are intrinsically safe, require little or no power, high-sensitivity, high-selectivity, without high-temperature heating for catalytic reactions, that also offer low cost and technical simplicity for cost-effective detection and visualization of fluids, including methane.